Stabilization of Inertia Wheel Pendulum using Multiple Sliding Surface Control Technique
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Transcript of Stabilization of Inertia Wheel Pendulum using Multiple Sliding Surface Control Technique
CRVCONTROL OF ROBOT AND VIBRATION LABORATORY
Stabilization of Inertia Wheel Pendulum using Multiple Sliding Surface Control
Technique
January 17, 2012
Speaker: Ittidej MoonmangmeeNo.6 Student ID: 5317500117
A paper from Multtopic Conference, 2006. INMIC’ 06. IEEE
By Nadeem Qaiser, Naeem Iqbal, and Naeem Qaiser
Dept. of Electrical Engineering, Dept. of Computer Science and Information technology, PIEAS
Islamabad, Pakistan
Key references for this presentation2/18
Textbook:
[3] Bongsob Song and J. Karl Hedrick,
Dynamic Surface Control of Uncertain Nonlinear Systems: An LMI Approach, Springer, New York, 2011.
Proceedings:
[1] M.W. Spong, P. Corke, and R. Lozano, “Nonlinear
Control of the Inertia Wheel Pendulum”, Automatica, 2000.PhD Thesis:
[2] Reza Olfati-Saber, Nonlinear Control of
Undeactuated Mechanical Systems with Application to Robotics and Aerospace Vehicles, MIT, PhD Thesis 2001.
Engineers & Mathematicians
Control Theory (or Mathematical Control Theory or Control Sciences)
Classifications & Styles of Control Paper
Control Application (or Control
Engineering)
Dynamic model Controller and/or observer design Experimental setup Simulations vs. experimental results
Engineers
Mathematicians are in a majority
Type 2: Problem formulation & Assumptions Mathematical proofs (rigorously):
definition, lemma, proposition, theorem, corollary, etc.
No experiments Illustrated examples Sometimes has no simulations
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Type 1: Dynamic model (a
benchmark) Controller and/or observer
design
Computer simulation via compare with other methods
Control Sciences
Stabilization of Inertia Wheel Pendulum using Multiple Sliding Surface Control
TechniqueControl Theory (or Mathematical Control Theory or Control Sciences)
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Outline
Underactuated Mechanical
Systems
Overview of Control System
Design
Dynamic Model
Controller Design
Stability Analysis
Simulation Results
Concluding Remarks
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1q
2q
2q
1q
2q
1q
Pendubot
Acrobot
Rotary Prismatic System
1q
2q
1q
2q
1q
2q
Inverted Pendulum
Rotational InvertedPendulum
Perpendicular RotationalInverted Pendulum
“Fish Robot”[Mason and Burdick, 2000]
3q
4q
1q2q
Fully actuated: #Control I/P = #DOF.Underactuated: #Control I/P < #DOF.
E
X
A
M
P
L
E
S
Underactuated Mechanical Systems
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Underactuated Mechanical Systems7/18
E
X
A
M
P
L
E
S
The Inertia-Wheel Pendulum
q1
q2I2
I1, L1g
[Spong et al, 2000]
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Single-Input-Single-Output (SISO) Nonlinear time-invariant Underactuated mechanical system Simple mechanical system
Euler-Lagrange (EL) equations of motion
Control System Architecture
Step 1:
Step 2:
Step 3:
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{
11 12 1 1 1 2 1 1
21 22 2
( )( ) ( )
2 211 1 1 2 1 1 2
12 21 2
11 1 12
( ) sin( ) 0
0 1
are constants
:
Q qM q g q
m m q ml mL g q
m m q
where m ml mL I I
and m m I
m q m
té ùé ù é ù éù- +ê úê ú ê ú êú+ =ê úê ú ê ú êúê úê ú ê ú êúë ûë û ë û ëû
= + + +
= =
+W
&&
&&14444244443 14444444444244444444443
&& &2 1 1 2 1 1
21 1 22 2
( ) sin( ) 0q ml mL g q
m q m q t
ìï - + =ïíï + =ïî
&
&& &&
q1
q2I2
I1, L1g
Dynamic Model
Step 1:
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1 1 2 1 3 2 4 2
1 2
2
3 4
4
, , ,
.....:
.....
Let x q x q x q and x q
x x
xStateequation
x x
x
t
t
= = = =ìï =ïïï = +ïïíï =ïïï = +ïïî
& &
&
&
&
&
Collocated Partial Feedback Linearization
11 12 1 1
21 22 2 2
( ) ( ) ( , ) 0:
( ) ( ) ( , )
m q m q q h q q
m q m q q h q q t
é ùé ù é ù é ùê úê ú ê ú ê úW + =ê úê ú ê ú ê úê úê ú ê ú ê úë ûë û ë û ë û
&& &
&& &
General Form of the EL Equations of Motion for an Underactuated Mechanical System: [Spong et al, 2000]
Remarks:
fully linearized system (using a change of control) Impossible partially linearized system (q2 transform into a double integrator) Possible after that, the new control u appears in the both (q1, p1) & (q2, p2) subsystems this procedure is called collocated partial linearization
Proposition There exists a global invertible change of control in the form
where
such that the dynamics of transformedto the partially linearized system.
( ) ( , )q u q qt a b= + &
122 21 11 12
12 21 11 1
( ) ( ) ( ) ( ) ( )
( , ) ( , ) ( ) ( ) ( , )
q m q m q m q m q
q q h q q m q m q h q q
a
b
-
-
= -
= -& & &( )
1 2
Configuration vector:
( ) underactuated coordinates
( ) actuated coordinates
[ , ] ,T n m m
n m
m
q q q -
-
= Î ´¡ ¡
Control vector:
( ) controlsm mt Î ¡
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Collocated Partial Feedback Linearization
1 11 1
1 0 0
new2 2
2 22
( , )( , ) ( )
:
( , )
q pq p nonlinear subsystem
p f q p g q
q pq p linear subsystem
p
ì üï ï=ï ïï ýï ï= +ï ïï þW í üï ï=ï ïï ýï ï=ï ïï þî
&
&
&
&
u
u
where (q) is an m m positive definite symmetric matrix and
10 11 12( ) (1) ( )g q m m q-= -
Define new state variables
Step 2:Transform to the Partial Feedback Linearization form
211 22 21 11
21 11 1 1 2 1 1
( , ) ( ) /( , ) ( ) where
( ) ( / )( ) sin( )
q q m m m mq q u q
q m m ml mL g q
at a b
b
ìï = -ïï= + íï = +ïïî
&&
1 11 1 12 2
2 1
3 2
(pendulum angle)
(wheel velocity)
z m q m q
z q
z q
ìï = +ïïï =íïï =ïïî
& &
&
New state equation in the Strict Feedback Form
( ) }1 1 1 2 1
122 1
11 113
3
2sin( ) ( )
(1
)
Nonlinaer Coreor Reduced
Linear orOu
z ml mL g
mz z
m
z
zer
uztm
ìï = +ïïï üï ïï ïí = - ïïï ýïï ïï ï=ï ïïþïî
&
&
&
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Controller Design13/18
Goal:Stabilizes 2 30, 0z z® ®
( ) }12
2 111 1
2
3
1 2
3
1 1 1
1
1
sin( )
&
&
&
mz z
Ou
z ml z
z
mL g Core
term mz u
üïï
ìïïïïïïí = - ïïýïï= ïïþ
ïï
î
= +
ïïïï
212
(positive definite)
(negative definite)
( ) 0
( ) 0i i
i i i
V z z
V z zz
= >
Þ = <& &
First Design the synthetic inputs z2d for thecore subsystem achieves the Lyapunov stability
Core Subsystem Controller Design
Step 3:
1 2 2dS z z= -
Second define the sliding surface
121 2 2 1 3 2
11 11
1d d
mS z z z z z
m m= - = - -& & & &
2 3 3dS z z= -
2 3 3 3d dS z z u z= - = -& & & &
Third Design again the synthetic I/P, z3d
To achieve this condition, we choose
113 1 1 1 2
12 11
1d d
mz K S z z
m m
æ ö÷ç ÷= + -ç ÷ç ÷÷çè ø&
Finally, the control law chosen to driveS2 0
3 2 2du z K S= -&
To achieve this condition, we choose1
2 1 2tan ( ), 0 , 0
dz a cz a cp-= - < £ >
Outer Subsystem Controller Design
Stability Results
{ 1 2 1
1 1 1 12 11 2
2 2 2
: sin( )
( / ):
N d
L
z z S
S K S m m S
S K S
S = +ìï = - -ïS íï = -ïî
&&
&
Theorem 1:
(N , L) is global asymptotic stability
1 1 1 12 11 2
2 2 2
( / ):
L
S K S m m S
S K S
ìï = - -ïS íï = -ïî
&
&
Theorem 3:
L is global asymptotic stability
L is global exponential stability
Proposition 1: N |S1 = 0 is globally Lipschitz.
{1
11 10
: sin( tan ( ))N S
z a cz-
=S =&
Theorem 2: N |S1 = 0 if 0 < a ≤ /2 and c > 0 then z1 = 0 is global asymptotic stability.
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Remark: we left out all of the proofs from the presentation
Plant parameters:
m11 = 4.83 10-3
m12 = m21 = m22 = 32 10-6
w = 379.26 10-3
Controller parameters:
a = /2, c = 9,K1 = 4, K2 = 6,
and T = 0.001
q1(0) =
I2
I1, L1
g
Initial state:
(q1(0), q2(0)) = (, 0)
q1(T) = 0g
I2
q2(T) = 0
I1, L1
Final state:
(q1(T), q2(T)) = (0, 0)
where the plant parameters are settedas same as in Olfati-Saber (2001) andSpong (2000).
Simulation Results15/18
Pendulum angle, velocity
Wheel velocity
time (second)
time (second)
2.2 sec
3 sec
time (second)
time (second)
Pendulum angle, velocity
Wheel velocity
3.6 sec
3.7 sec
[Olfa
ti-Sab
er, 2
001]
VS
Simulation ResultsM
SS
Con
troll
er
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[Olfati-Saber, 2001]
VS
time (second)
Control effort (Nm)
Simulation Results
time (second)
Control effort (Nm)
0.43 Nm 0.33 Nm
MSS Controller
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Concluding Remarks18/18
The collocated partial feedback linearization was presented for transform a nonlinear underactuated mechanical system into the strict feedback form
A Multiple Sliding Surface controller is designed to
achieves global asymptotically stable of the pendulum angle and the wheel velocity (neglect the wheel angle)
The MSS has advantages that the two controllers, i.e. no supervisory switching required as in Spong’s
design(2000) (more simple structure)
the response is faster than the designs by Olfati-Saber (2001) (more better performance)
However, more control effort required for MSS
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CONTROL OF ROBOT AND VIBRATION LABORATORY
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